Abstract

Traction Force Microscopy (TFM) is a powerful approach for quantifying cell-material interactions that over the last two decades has contributed significantly to our understanding of cellular mechanosensing and mechanotransduction. In addition, recent advances in three-dimensional (3D) imaging and traction force analysis (3D TFM) have highlighted the significance of the third dimension in influencing various cellular processes. Yet irrespective of dimensionality, almost all TFM approaches have relied on a linear elastic theory framework to calculate cell surface tractions. Here we present a new high resolution 3D TFM algorithm which utilizes a large deformation formulation to quantify cellular displacement fields with unprecedented resolution. The results feature some of the first experimental evidence that cells are indeed capable of exerting large material deformations, which require the formulation of a new theoretical TFM framework to accurately calculate the traction forces. Based on our previous 3D TFM technique, we reformulate our approach to accurately account for large material deformation and quantitatively contrast and compare both linear and large deformation frameworks as a function of the applied cell deformation. Particular attention is paid in estimating the accuracy penalty associated with utilizing a traditional linear elastic approach in the presence of large deformation gradients.

Highlights

  • Traction Force Microscopy (TFM) is a powerful methodology of quantifying cellular forces during cell-material interactions

  • The large deformation 3D TFM (LD 3D TFM) methodology presented in this paper consists of two basic components, analogous to our previous small deformation 3D TFM (SD 3D TFM) technique

  • Fig. 1(A) presents the cell displacement analyzed with our previous digital volume correlation (DVC) algorithm [21], whereas Fig. 1(B) shows the results analyzed with our high resolution fast iterative digital volume correlation algorithm (FIDVC) technique [20]

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Summary

Introduction

Traction Force Microscopy (TFM) is a powerful methodology of quantifying cellular forces during cell-material interactions. TFM computes cell-generated surface tractions from a set of measured cell-induced displacement fields that are typically recorded by using either a single particle tracking or image correlation approach, such as digital image (2D) or digital volume (3D) correlation [2,6,9,10,11,12,13]. Image correlation techniques are generally advantageous over single particle tracking algorithms if a high enough fiducial tracker particle density can be achieved. They are generally less prone to error in the presence of noise and they can be readily computationally implemented. One can utilize a finite element framework to compute surface tractions from the measured displacement values [10,17]

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